1. Field of the Invention
The present invention relates to an MRI (magnetic resonance imaging) apparatus and a flow quantification method with regard to ASL (arterial spin labeling) imaging, which can quantify flow with a simple method using imaging based upon the ASL method which can provide images of perfusion or blood vessels, without administrating a contrast medium. It is noted that the ASL method described in the present invention indicates all the spin labeling methods in the broad sense.
2. Description of the Related Art
Magnetic resonance imaging is a method wherein nuclear spins of a subject in a static magnetic field are magnetically excited by radio frequency (RF) signals with a Larmor frequency so as to obtain an image from FID (self induced decay) signals or echo signals, accompanying the excitation.
As one category of magnetic resonance imaging, the spin labeling method, i.e., the ASL method for evaluating perfusion for tissue has been known. The ASL method is a method for providing perfusion images and the like, reflecting the blood vessel image or micro circulation of a subject, without administering a contrast medium, i.e., in a noninvasive manner, and in recent years, research has been actively made with regard to the ASL method. In particular, clinical applications have been made mainly with regard to cerebral blood flow (CBF) of the head, and furthermore, quantification of blood flow is becoming possible.
The ASL method is roughly classified into the continuous ASL (CASL) method and the pulsed ASL (PASL) method (also referred to as dynamic ASL (DASL)). The CASL method is a method wherein great, continuous, and adiabatic RF is applied, the spin state within blood vessels is labeled (magnetized) at a certain point in time, and the change in signals following the labeled-blood bolus reaching an imaging slab (observation face) is imaged. On the other hand, the PASL method is a method wherein pulse-shaped adiabatic RF, the magnetization in blood vessels is changed at all times, and imaging is performed for the tissue having magnetized blood flow continuously, thereby evaluating the perfusion of the tissue. The PASL method can be relatively easily performed with a clinical-use MRI apparatus.
With the ASL imaging, in general, two images of the control mode and the label (tag) mode are generated. The image data sets obtained with the tag mode and the control mode are subjected to difference calculation for each pixel between these images. As a result, information with regard to blood flowing into the imaging slab, i.e., an ASL image indicating circulation can be obtained.
Attempts to quantify flow (perfusion) using the above-described ASL imaging are known. An example thereof will be described.
In general, the flow f is obtained from the equation which is referred to as the Bloch equation. (See “MRM 35: 540-546 (1996), C. Scwarzwauer et al”, for example.) The longitudinal (lattice-spin or T1)-relaxation Bloch equation, which is usable when there is a flow “f,” is represented with Expression (a).dM/dt=(M0−M)T1+f·(Ma−M/λ)  (a)
wherein λ is the cerebral blood flow distribution coefficient of water (0.9 to 1),
wherein M is the pixel value of the tissue image,
wherein Ma is the longitudinal magnetization density,
wherein M0 is the pixel value of tissue image under saturation (proton density image), and
wherein T1 is the tissue T1 (longitudinal or spin-lattice) relaxation time value.
Also, the following expression holds.1/T1app=1/T1+f/λ  (b)
wherein T1app is the apparent T1.
Thus, images are obtained with the tag mode and the control mode, respectively, whereby the flow f is calculated. That is, M0 and T1 are measured for each pixel, and reckoning T1 in blood (which is equal to T1a: the suffix “a” indicates artery) to be the same as T1 in tissue, it has been reported that the flow f is represented with the following expression.f∝λ·ΔS/{2·TI·M0·exp(−TI/Tapp)}  (c)
wherein ΔS is the pixel value (=Scont−Stag) of the ASL image, and
wherein TI is the inversion time.
However, in practice, there is the need to measure M0 and T1 for each pixel for calculating the flow f according to the above-described Expression (c), so measurement is troublesome, a great amount of data is required, and also the calculation amount is great, leading to an increase in calculating time.
Furthermore, it is known that due to a great number of image data sets containing time difference in acquisition, being used, misregistration or the like occurs due to the body motion, and accordingly, deterioration of measurement precision is caused due to the margin of error occurring from this point.
As described above, there are various problems encountered when applying the conventional flow (perfusion) quantification method to clinical practice, so quantification wherein these problems are solved and practical use can be made is desired. In particular, in the event of applying the method to a patient affected with acute stage infarction, there is the need to easily and quickly quantify flow.
Taking the above-described situation into consideration, a method wherein the gathered data obtained from an imaging slab with ASL imaging can be kept to a minimum, and linear scaling is performed using the gathered data, thereby easily quantifying flow (perfusion) on an imaging slab, is proposed in Japanese Unexamined (Laid-open) Patent Application Publication No. 11-375237.
However, the flow quantification method disclosed in the aforementioned application is a method which is related to the “single-compartment model”, upon which the Bloch equation is based. The single-compartment model is based upon an assumption that water, which is a tracer for ASL, has the nature of complete diffusion. That is, the single-compartment model is based upon a precondition that the water spins in artery blood flow transported to tissue are rapidly transferred into the tissue and the spins of water in the artery blood provide T1 values of the tissue.
However, in practice, such conditions are never satisfied completely during the time period from labeling of upstream artery blood flow up to the beginning of data acquisition (a time period T1 (in practice, around one to two seconds)). The reason is that the number of the water spins left on the capillary vessel bed is greater than that of the water spins outside the capillary vessel. Accordingly, the above-described quantified flow value readily contains a margin of error due to the preconditions not being satisfied completely, upon which the single-compartment model is based, and accordingly, a flow quantification method with higher precision is desired.
On the other hand, study with regard to a model with higher precision as compared with the single-compartment model is being undertaken as shown in the document “Jinyuan Z, David A W, Peter C M: Two-compartment model for perfusion quantification using Arterial Spin Labeling, Proc. Intl. Soc. Magn. Reson. Med., 2000; 8, 166”. However, the more complex the model becomes, the greater the number of parameters required for the flow quantification is, leading to calculation being more complex.
On the other hand, in experiment, it has been reported that the ASL signal intensity approximately linearly correlates to the blood flow in experiments on animals and so forth.